Senior Agentic AI Security Engineer - Remote & Trusted AI

LTS; United States; Remote; USD 152,000 - 184,000; Full time

Job summary

LTS in the United States — Remote is seeking a highly skilled Senior Agentic AI Security Engineer to design safeguards for AI agents, retrieval pipelines, prompts, tools, memory, and model interactions, ensuring explainability, auditable trails, and compliance with FedRAMP and healthcare requirements.

You will collaborate with AI architects, software and platform engineers, and product leaders to embed security into development from experimentation to production, balancing innovation with

Qualifications

• Bachelor's degree in CS, cybersecurity, AI, software engineering, information security, or related field.
• 7+ years of software engineering, cybersecurity engineering, AI engineering, or application security experience.
• Experience designing secure cloud-native or distributed software systems.
• Experience with Large Language Models (LLMs), AI applications, or Agentic AI platforms.
• Experience securing APIs, microservices, and enterprise applications.
• Knowledge of OWASP Top 10 and secure software development practices.
• Understanding of AI-specific security risks including prompt injection, jailbreaking, data poisoning, model abuse, adversarial inputs, hallucinations, and sensitive data leakage.
• Experience with cloud security across AWS, Azure, or Google Cloud.

Responsibilities

• Design and implement security controls for autonomous and multi-agent AI systems.
• Secure agent orchestration, tool execution, memory, and external integrations.
• Identify and mitigate emerging AI-specific attack vectors and vulnerabilities.
• Secure Retrieval-Augmented Generation (RAG) pipelines, embeddings, vector databases, and enterprise knowledge repositories.
• Design controls to prevent unauthorized knowledge access, data leakage, and information exposure.
• Implement secure handling of sensitive enterprise and healthcare data throughout AI workflows.
• Perform threat modeling for AI applications, agent architectures, prompts, APIs, and retrieval systems.
• Assess risks associated with prompt injection, jailbreak attempts, indirect prompt attacks, tool misuse, hallucinations, data poisoning, model abuse, and adversarial inputs.
• Develop mitigation strategies that reduce AI-specific security risks while maintaining usability.
• Build guardrails that improve trustworthy AI behavior.
• Design policy enforcement, human-in-the-loop approval workflows, content filtering, and AI governance mechanisms.
• Help define organizational standards for responsible AI development and deployment.
• Design monitoring capabilities to detect abnormal agent behavior, misuse, prompt manipulation, and anomalous model interactions.
• Implement logging, traceability, and audit capabilities supporting explainability and regulatory compliance.
• Build mechanisms for continuous AI risk assessment and operational visibility.
• Partner with software engineers to integrate AI security into development workflows.
• Conduct security reviews of AI features before production deployment.
• Promote secure AI engineering practices across the product organization.

Skills

7+ years experience

Python or TypeScript

Cloud security (AWS/Azure/GCP)

LLMs / AI security

APIs & microservices security

OWASP Top 10

Secure SDLC / DevSecOps

Threat modeling

Education

Bachelor's degree in CS/ cybersecurity/ AI/ software engineering/ information security or related

Tools

LangGraph

LangChain

CrewAI

Semantic Kernel

AutoGen

LlamaIndex

Pinecone

Weaviate

Qdrant

Milvus

Azure AI Search

Job description

LTS in the United States — Remote is seeking a highly skilled Senior Agentic AI Security Engineer to design safeguards for AI agents, retrieval pipelines, prompts, tools, memory, and model interactions, ensuring explainability, auditable trails, and compliance with FedRAMP and healthcare requirements.

You will collaborate with AI architects, software and platform engineers, and product leaders to embed security into development from experimentation to production, balancing innovation with